import gradio as gr
from transformers import pipeline
from datetime import datetime
import random

# -------------------------------------------------
# 🎯 MODEL INITIALIZATION
# -------------------------------------------------
MODEL_NAME = "superb/hubert-large-superb-er"
emotion_classifier = pipeline("audio-classification", model=MODEL_NAME)

# -------------------------------------------------
# 😄 EMOTION MAP + COLORS
# -------------------------------------------------
EMOTION_MAP = {
    "ang": ("Angry", "😡", "#ff4d4d"),
    "hap": ("Happy", "😄", "#4caf50"),
    "neu": ("Neutral", "😐", "#9e9e9e"),
    "sad": ("Sad", "😢", "#2196f3"),
    "exc": ("Excited", "🤩", "#ff9800"),
    "fru": ("Frustrated", "😤", "#f44336"),
    "fea": ("Fearful", "😨", "#673ab7"),
    "sur": ("Surprised", "😲", "#00bcd4"),
    "dis": ("Disgusted", "🤢", "#8bc34a"),
}

# -------------------------------------------------
# 🧠 EMOTION ANALYSIS
# -------------------------------------------------
def analyze_emotion(audio, team, purpose):
    if audio is None:
        return "<p style='color:red;'>⚠️ Please record or upload audio first.</p>", None

    if team == "Other":
        team = "Custom/Unspecified"
    if purpose == "Other":
        purpose = "Custom/Unspecified"

    results = emotion_classifier(audio)
    results = sorted(results, key=lambda x: x["score"], reverse=True)
    top = results[0]
    label, emoji, color = EMOTION_MAP.get(top["label"], (top["label"], "🎭", "#607d8b"))
    score = round(top["score"] * 100, 2)

    dashboard_html = f"""
    <div style="text-align:center; padding:15px;">
        <h2>🏢 <b>{team}</b> | 🎯 <b>{purpose}</b></h2>
        <h3 style="color:{color}; font-size:26px;">{emoji} {label.upper()} — {score}%</h3>
        <p style="color:#666;">Detected Emotion Intensity (Confidence)</p>
        <div style="width:85%; margin:auto; background:#eee; border-radius:20px;">
            <div style="width:{score}%; background:{color}; height:20px; border-radius:20px;"></div>
        </div>
        <br>
        <h4>📊 Full Emotion Breakdown</h4>
        <ul style="list-style:none; padding:0;">
    """
    for r in results:
        lbl, emo, clr = EMOTION_MAP.get(r["label"], (r["label"], "🎭", "#777"))
        scr = round(r["score"] * 100, 2)
        dashboard_html += f"<li>{emo} <b>{lbl}</b>: {scr}%</li>"
    dashboard_html += "</ul><hr>"

    insights = random.choice([
        "🧩 Team seems calm and balanced today. Great stability!",
        "⚡ Slight emotional tension detected. Consider quick sync-up meetings.",
        "💬 High positive tone — keep up the good team energy!",
        "🚨 Stress indicators detected. HR may follow up proactively.",
        "📈 Emotion variation is rising — review workloads or deadlines."
    ])

    insight_html = f"""
    <div style="background:#f5f5f5; padding:15px; border-radius:12px;
                margin-top:15px; border-left:6px solid #4a90e2;
                box-shadow:0 2px 6px rgba(0,0,0,0.05);">
        <h4 style="color:#222; margin-bottom:6px;">🧠 AI Insight</h4>
        <p style="color:#333; font-size:16px; font-weight:500;">{insights}</p>
        <p style="font-size:13px; color:#777;">(Demo mode — not stored to any database)</p>
    </div>
    """
    return dashboard_html, insight_html


# -------------------------------------------------
# 🎨 GRADIO UI ELEMENTS
# -------------------------------------------------
DEPARTMENTS = ["Test","Procurement", "Logistics", "Planning", "Inventory", "Distribution", "HR", "Other"]
PURPOSES = ["Test","HR Meeting", "Team Stand-up", "One-on-One", "Customer Call", "Interview", "Other"]

disclaimer_html = """
<div style="display:flex; align-items:center; background:linear-gradient(135deg, #fff8e1, #fff3cd);
            padding:15px; border-radius:12px; margin-top:20px; border-left:8px solid #ff9800;
            box-shadow:0 2px 6px rgba(0,0,0,0.1);">
    <div style="font-size:28px; margin-right:12px; color:#ff9800;">💡</div>
    <div>
        <h3 style="color:#d35400; margin:0 0 5px 0;">Demo Disclaimer</h3>
        <p style="color:#333; font-size:15px; line-height:1.6; margin:0;">
            This is a <b style="color:#e65100;">demonstration version</b> created for HR and leadership showcases.<br>
            Your voice data is 
            <b style="background-color:#fffbe6; color:#c0392b; padding:2px 6px; border-radius:4px;">
            NOT being saved or shared
            </b> anywhere.<br>
            Database logging is <b style="color:#e65100;">simulated</b> — you can record or upload audio freely.<br>
            ✅ Safe to explore and test in this environment.
        </p>
    </div>
</div>
"""

# -------------------------------------------------
# 🚀 APP INTERFACE WITH INLINE LOADING
# -------------------------------------------------
with gr.Blocks(theme=gr.themes.Soft()) as app:
    gr.HTML("""
    <div style="text-align:center; padding:20px;">
        <h1>🎧 SCM Emotion Intelligence Dashboard</h1>
        <p style="font-size:16px; color:#555;">
            Analyze uploaded or recorded team meeting audio to understand the emotional tone of employees.<br>
            Built for HR and Managers to assess engagement and team well-being.
        </p>
    </div>
    """)

    with gr.Row(equal_height=True):
        with gr.Column(scale=1, min_width=380):
            audio_input = gr.Audio(
                sources=["microphone", "upload"],
                type="filepath",
                label="🎙️ Record or Upload Audio",
            )
            team_input = gr.Dropdown(DEPARTMENTS, label="🏢 Select Team / Department")
            purpose_input = gr.Dropdown(PURPOSES, label="🎯 Purpose of Audio")
            analyze_btn = gr.Button("🚀 Analyze Emotion", variant="primary")

            gr.HTML(disclaimer_html)

        with gr.Column(scale=2, min_width=550):
            output_html = gr.HTML("""
                <div style='text-align:center; padding:30px; color:#999;'>
                    <p>Awaiting input... Upload or record to begin analysis.</p>
                </div>
            """)
            insight_html = gr.HTML()

    # Inline loader — replaces dashboard temporarily
    def process_with_loader(audio, team, purpose):
        loader_html = """
        <div style='text-align:center; padding:60px;'>
            <div style='margin:auto; border:6px solid #eee; border-top:6px solid #4a90e2;
                        border-radius:50%; width:50px; height:50px; animation:spin 1s linear infinite;'></div>
            <h3 style='color:#333; margin-top:20px;'>⏳ Analyzing your audio...</h3>
            <p style='color:#777;'>This may take a few seconds depending on file size.</p>
            <style>@keyframes spin {0%{transform:rotate(0deg);}100%{transform:rotate(360deg);}}</style>
        </div>
        """
        yield loader_html, None
        dashboard_html, insight_html = analyze_emotion(audio, team, purpose)
        yield dashboard_html, insight_html

    analyze_btn.click(
        fn=process_with_loader,
        inputs=[audio_input, team_input, purpose_input],
        outputs=[output_html, insight_html],
    )

    gr.HTML("""
    <hr>
    <p style="text-align:center; color:#999; font-size:14px;">
        💾 (Demo Mode) Database integration coming soon for Power BI visualization.<br>
        Presented by <b>Dhrubo Bhattacharjee</b>
    </p>
    """)

# -------------------------------------------------
# 🏁 LAUNCH APP
# -------------------------------------------------
if __name__ == "__main__":
    app.launch(server_name="0.0.0.0", server_port=7860)